CAREER: Coupling Geometry Acquisition and Digital Fabrication

职业：几何采集和数字制造的耦合

• 批准号: 1652515
• 负责人: Daniele Panozzo
• 金额: $ 55.38万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-02-01 至 2022-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1652515&HistoricalAwards=false
• 关键词: CAREER; Coupling; Geometry; Acquisition; Digital

3D scanning and digital fabrication technologies are rapidly evolving, and their combination has the potential to dramatically change the way we design functional objects by enabling the fabrication of objects with an unprecedented geometrical complexity while drastically speeding up the design iterations. The goal of this project is to lay the algorithmic foundation for tightly integrating 3D scanning and digital fabrication, to support new applications in life sciences and medicine. To this end, the research will transform the traditional geometry processing pipeline by proposing a new data representation and new algorithms specifically designed to support fabrication and scanning. In contrast to traditional global optimization methods, which struggle to deal with massive and noisy datasets, the PI focuses on semi-local algorithms that are robust, easy to parallelize and have a small memory footprint. The research will have two major thrusts: Scanning for Fabrication (ScanFab), and Fabrication for Scanning (FabScan). The ScanFab pipeline will support medical applications that require the design of customized medical devices and prostheses; to validate its effectiveness, the PI will collaborate with corporate partner Sonova to acquire and reconstruct the geometry of the ear canal, and to provide interactive techniques for designing the next generation of customized hearing aids. The FabScan thrust will lead to the development of a novel microscopy technique for estimating 2D and 3D traction forces on the surface of cells, which will be fundamental to understanding cell migration in development and cancer genesis; the technique will be developed in collaboration with the Dept. of Mechanical and Process Engineering at ETH Zurich, and will be evaluated in a large biological study in collaboration with the medical school in the University of Milano. The developed techniques will be integrated into the PI's open-source library, to allow the research community to directly benefit from these contributions.In ScanFab, the PI introduces an integrated pipeline to acquire, modify, simulate, and fabricate a variant of an existing 3D object. The pipeline is based on T-meshes, a geometrical representation that combines the benefits of coarse and highly structured quadrilateral meshes with the efficiency and flexibility of triangle meshes. The research will tackle: (1) the interactive and out-of-core conversion of point clouds to T-meshes; (2) the interactive editing of the reconstructed surfaces while ensuring fabricability; (3) the physical simulation of the new geometry to study its mechanical properties before fabrication, using a Finite Element Method (FEM). In FabScan, the pipeline will be reversed to sense forces at the microscopic level. The PI will fabricate a microstructure with a known geometry and physical properties, apply loads to it, and then acquire the deformed geometry via 3D confocal microscopy. The traction forces will be accurately reconstructed by solving an inverse FEM problem, combining the knowledge of the initial and of the deformed geometry.

3D扫描和数字制造技术正在迅速发展，它们的结合有可能极大地改变我们设计功能性物体的方式，使物体的制造具有前所未有的几何复杂性，同时大大加快设计迭代。 该项目的目标是为紧密集成3D扫描和数字制造奠定算法基础，以支持生命科学和医学领域的新应用。 为此，该研究将通过提出新的数据表示和专门设计用于支持制造和扫描的新算法来改变传统的几何处理管道。 与传统的全局优化方法相比，PI专注于半局部算法，这些算法具有鲁棒性，易于并行化并且内存占用小。 该研究将有两个主要方向：扫描制造（ScanFab）和扫描制造（FabScan）。 ScanFab管道将支持需要设计定制医疗设备和假体的医疗应用;为了验证其有效性，PI将与企业合作伙伴Sonova合作，获取和重建耳道的几何形状，并为设计下一代定制助听器提供交互技术。 FabScan推力将导致开发一种新的显微镜技术，用于估计细胞表面的2D和3D牵引力，这将是理解发育和癌症发生中细胞迁移的基础;该技术将与Dept.合作开发。在苏黎世联邦理工学院的机械和过程工程，并将在一个大型生物研究与米兰大学医学院合作进行评估。 开发的技术将被集成到PI的开源库中，使研究社区能够直接受益于这些贡献。在ScanFab中，PI引入了一个集成的管道来获取、修改、模拟和制造现有3D对象的变体。 管道基于T-网格，这是一种几何表示，结合了粗糙和高度结构化的四边形网格的优点和三角形网格的效率和灵活性。 该研究将解决：（1）点云到T网格的交互式和核心外转换;（2）重建表面的交互式编辑，同时确保可制造性;（3）新几何形状的物理模拟，以在制造前使用有限元法（FEM）研究其机械性能。 在FabScan中，管道将被反转以在微观水平上感测力。 PI将制造具有已知几何形状和物理特性的微结构，向其施加载荷，然后通过3D共聚焦显微镜获取变形的几何形状。 牵引力将被准确地重建通过求解逆有限元问题，结合知识的初始和变形的几何形状。

项目成果

Deformation Capture via Soft and Stretchable Sensor Arrays

• DOI: 10.1145/3311972
• 发表时间: 2019-04-01
• 期刊: ACM TRANSACTIONS ON GRAPHICS
• 影响因子: 6.2
• 作者: Glauser, Oliver;Panozzo, Daniele;Sorkine-Hornung, Olga
• 通讯作者: Sorkine-Hornung, Olga

Half-Space Power Diagrams and Discrete Surface Offsets

• DOI: 10.1109/tvcg.2019.2945961
• 发表时间: 2018-04
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: Zhen Chen;Daniele Panozzo;Jérémie Dumas

Poly-Spline Finite-Element Method

• DOI: 10.1145/3313797
• 发表时间: 2018-04
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: T. Schneider;Jérémie Dumas;Xifeng Gao;M. Botsch;Daniele Panozzo;D. Zorin

Exact and efficient polyhedral envelope containment check

• DOI: 10.1145/3386569.3392426
• 发表时间: 2020-07
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: Bolun Wang;T. Schneider;Yixin Hu;M. Attene;Daniele Panozzo

Sparsity-Specific Code Optimization using Expression Trees

• DOI: 10.1145/3520484
• 发表时间: 2021-10
• 期刊: ACM Transactions on Graphics (TOG)
• 作者: Philipp Herholz;Xuan Tang;T. Schneider;Shoaib Kamil;Daniele Panozzo;O. Sorkine-Hornung